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This guy cracked the code on AI girlfriend monetization using real-time technology and now pulls $76,000 per month from one Instagram profile without ever showing his real face or hiring an actual model. He got tired of watching creators split 80 percent of revenue with agencies while their competitors...

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20,831 views • 2 months ago •via X (Twitter)

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This guy cracked the code on AI-powered fashion ecommerce using synthetic face technology and now pulls $50,000 to $150,000 per month from two Shopify stores without paying a single real model. He got tired of watching DTC fashion brands burn $20,000 monthly on photoshoots while their competitors tested 40 product angles in the same timeframe, so he built a system that generates hyperrealistic fashion content using his gaming PC and real-time AI masks instead of studios, contracts, or casting calls. His monthly profit hit $150,000 last month from just 2 stores and organic TikTok traffic, while traditional fashion brands cap out at $30K after paying models $400 to $800 per shoot and studio rentals of $200 to $500 per session. Here is the exact breakdown: → Real-time synthetic face technology becomes the only tool you need, but most people butcher the setup by skipping motion sync calibration in the first 30 seconds → Product selection comes first, and if you mess this up nothing saves it. Stick to women's accessories (bags, sunglasses, jewelry) because that is where organic TikTok engagement lives → Avatar casting is not random. You build one consistent AI face that repeats across all content so your audience recognizes the "model" and trusts the brand continuity → You are picking who your customer projects onto, not who looks expensive. That is your positioning baked into the face → Motion capture runs before generation, and this is what kills the uncanny valley effect that destroys watch time in 4 seconds → You mirror your own gestures through webcam: wave, chin tap, finger point, shoulder dance. The AI mask tracks every micro-movement and applies it to the generated face in real time → Batching is the move 94 percent skip: same outfit base, multiple product swaps, one recording session. No re-shooting, no model schedules, no usage rights negotiations → The system generates 3 to 5 TikToks before lunch, while traditional brands test 2 per week and wonder why their conversion rates are stuck at 0.8 percent The economics are stupid: each video costs him $0 in talent fees, pulls 1.5 million views organically, converts at 0.03 percent into 450 orders at $45 to $60 retail with $30 to $45 margin per sale. That is $15,750 profit per viral video, while fashion brands pay $1,200 per shoot and net $3,000 after ads. The key move nobody talks about: you cannot skip the motion synchronization test. If you generate the AI face without mirroring your own natural gestures first, the avatar moves like a mannequin. The blinks lag. The smile timing breaks. The whole thing screams "synthetic face technology" and your hook rate dies at 1.1 seconds. His system records him doing the exact dance trend first, so the AI mask inherits human timing, natural head tilts, and spontaneous energy that reads as a real creator showing off a product find, not a rendered advertisement. One accessories store generated 10 variants of the same handbag reveal in 18 minutes with different outfits, different backgrounds, different trend audios, and found the winner in 72 hours without spending $6,000 on influencer gifting. They were previously paying $800 per UGC creator and burning $4,800 per week on content that plateaued at 40K views. Now they spend $0 for 10 variants and their cost per acquisition dropped from $62 to $18. UGC agencies now panic because their entire margin was built on talent scarcity, and this removes the human bottleneck. The outfit changes between clips like a wardrobe filter. The lighting matches bedroom setups. The hand gestures sync with beat drops. No casting call. No model release. No location permits. Just a webcamera, a real-time AI mask, and the discipline to batch-test product angles before you commit ad spend to one creative.
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This guy cracked the code on AI-powered fashion ecommerce using synthetic face technology and now pulls $50,000 to $150,000 per month from two Shopify stores without paying a single real model. He got tired of watching DTC fashion brands burn $20,000 monthly on photoshoots while their competitors tested 40 product angles in the same timeframe, so he built a system that generates hyperrealistic fashion content using his gaming PC and real-time AI masks instead of studios, contracts, or casting calls. His monthly profit hit $150,000 last month from just 2 stores and organic TikTok traffic, while traditional fashion brands cap out at $30K after paying models $400 to $800 per shoot and studio rentals of $200 to $500 per session. Here is the exact breakdown: → Real-time synthetic face technology becomes the only tool you need, but most people butcher the setup by skipping motion sync calibration in the first 30 seconds → Product selection comes first, and if you mess this up nothing saves it. Stick to women's accessories (bags, sunglasses, jewelry) because that is where organic TikTok engagement lives → Avatar casting is not random. You build one consistent AI face that repeats across all content so your audience recognizes the "model" and trusts the brand continuity → You are picking who your customer projects onto, not who looks expensive. That is your positioning baked into the face → Motion capture runs before generation, and this is what kills the uncanny valley effect that destroys watch time in 4 seconds → You mirror your own gestures through webcam: wave, chin tap, finger point, shoulder dance. The AI mask tracks every micro-movement and applies it to the generated face in real time → Batching is the move 94 percent skip: same outfit base, multiple product swaps, one recording session. No re-shooting, no model schedules, no usage rights negotiations → The system generates 3 to 5 TikToks before lunch, while traditional brands test 2 per week and wonder why their conversion rates are stuck at 0.8 percent The economics are stupid: each video costs him $0 in talent fees, pulls 1.5 million views organically, converts at 0.03 percent into 450 orders at $45 to $60 retail with $30 to $45 margin per sale. That is $15,750 profit per viral video, while fashion brands pay $1,200 per shoot and net $3,000 after ads. The key move nobody talks about: you cannot skip the motion synchronization test. If you generate the AI face without mirroring your own natural gestures first, the avatar moves like a mannequin. The blinks lag. The smile timing breaks. The whole thing screams "synthetic face technology" and your hook rate dies at 1.1 seconds. His system records him doing the exact dance trend first, so the AI mask inherits human timing, natural head tilts, and spontaneous energy that reads as a real creator showing off a product find, not a rendered advertisement. One accessories store generated 10 variants of the same handbag reveal in 18 minutes with different outfits, different backgrounds, different trend audios, and found the winner in 72 hours without spending $6,000 on influencer gifting. They were previously paying $800 per UGC creator and burning $4,800 per week on content that plateaued at 40K views. Now they spend $0 for 10 variants and their cost per acquisition dropped from $62 to $18. UGC agencies now panic because their entire margin was built on talent scarcity, and this removes the human bottleneck. The outfit changes between clips like a wardrobe filter. The lighting matches bedroom setups. The hand gestures sync with beat drops. No casting call. No model release. No location permits. Just a webcamera, a real-time AI mask, and the discipline to batch-test product angles before you commit ad spend to one creative.

Shade

20,190 views • 2 months ago

This guy cracked the code on AI virtual influencers using real-time face filters and now D2C brands pay him $2,000 per UGC video. He got tired of watching D2C brands burn $4,000 on a single creator who takes 2 weeks to deliver one angle, so he built a setup that runs hyperrealistic AI girls in real-time from his own webcam, generating viral content without actresses, studios, or makeup artists. His monthly revenue hit $89,000 last month from a network of 7 AI personas across TikTok and Instagram, while the average UGC creator caps at $6K juggling 4 brand deals. Here is the exact breakdown: → The hardware is the moat, but most people butcher the setup in the first frame. You need the face mesh locked at 60fps with zero artifacting → Persona comes first, and if you mess this up nothing saves it. Name, backstory, voice tone, niche before a single clip is shot → Face selection is not random. You A/B test features (eye spacing, jawline, hair contrast with face-framing highlights) because some faces convert better in 9:16 → You are picking who your audience trusts, not who looks cool. That is your targeting baked into bone structure → Real-time physics run before the script, and this is what kills the uncanny valley that destroys watch time in 2 seconds → The filter has to survive the strap of a tank top, the texture of a knit cardigan, the hair flick. → Batching is the move 96 percent skip: one performance, multiple personas, three platforms. → The system pushes 12 pieces of content before lunch, while traditional brands test 2 creators per week and wonder why their CPAs are stuck at $94 The economics are stupid: each video costs him $4 in compute, sells for $1,500 to $3,000, and takes 14 minutes to produce. That is a 37,500 percent margin, while UGC agencies pay creators $400 to $800 per clip and net $200 after revisions. One supplement brand generated 14 variants with 7 personas in 4 hours and found a winner in 36 hours without flying a creator to LA. They were previously paying $1,200 per UGC video and burning $6,000 per week on content that did not scale. Now they spend $210 for 14 variants and their CPA dropped from $89 to $27. The avatars hold real products. Warm window light on the persona, cold neon on the operator. Mouth shapes sync to consonants, not just vowels. Just a webcam, a tracked face, and the discipline to move enough that the filter never has a chance to break.
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This guy cracked the code on AI virtual influencers using real-time face filters and now D2C brands pay him $2,000 per UGC video. He got tired of watching D2C brands burn $4,000 on a single creator who takes 2 weeks to deliver one angle, so he built a setup that runs hyperrealistic AI girls in real-time from his own webcam, generating viral content without actresses, studios, or makeup artists. His monthly revenue hit $89,000 last month from a network of 7 AI personas across TikTok and Instagram, while the average UGC creator caps at $6K juggling 4 brand deals. Here is the exact breakdown: → The hardware is the moat, but most people butcher the setup in the first frame. You need the face mesh locked at 60fps with zero artifacting → Persona comes first, and if you mess this up nothing saves it. Name, backstory, voice tone, niche before a single clip is shot → Face selection is not random. You A/B test features (eye spacing, jawline, hair contrast with face-framing highlights) because some faces convert better in 9:16 → You are picking who your audience trusts, not who looks cool. That is your targeting baked into bone structure → Real-time physics run before the script, and this is what kills the uncanny valley that destroys watch time in 2 seconds → The filter has to survive the strap of a tank top, the texture of a knit cardigan, the hair flick. → Batching is the move 96 percent skip: one performance, multiple personas, three platforms. → The system pushes 12 pieces of content before lunch, while traditional brands test 2 creators per week and wonder why their CPAs are stuck at $94 The economics are stupid: each video costs him $4 in compute, sells for $1,500 to $3,000, and takes 14 minutes to produce. That is a 37,500 percent margin, while UGC agencies pay creators $400 to $800 per clip and net $200 after revisions. One supplement brand generated 14 variants with 7 personas in 4 hours and found a winner in 36 hours without flying a creator to LA. They were previously paying $1,200 per UGC video and burning $6,000 per week on content that did not scale. Now they spend $210 for 14 variants and their CPA dropped from $89 to $27. The avatars hold real products. Warm window light on the persona, cold neon on the operator. Mouth shapes sync to consonants, not just vowels. Just a webcam, a tracked face, and the discipline to move enough that the filter never has a chance to break.

Shade

135,682 views • 2 months ago

A 40-YEAR-OLD CHINESE MAN TURNED HIMSELF INTO AN AI GIRL AND BUILT A $4.7K/MONTH FANVUE FUNNEL he started with one face-swap clip. same room, same body, same camera, but the output looked like a completely different creator. not a filter, not cosplay, an ai identity built on top of his own footage the workflow is stupidly simple: claude picks the character, niche and visual style. comfyui generates the face, flux makes the content bank, kling turns still images into reels and capcut pushes out dozens of short clips the article breaks the system down: first month barely cleared $420, second month jumped to $4,700 after one reel crossed 600,000 views. the account reached 800 followers and 50 fanvue subscribers before the real automation even started the fanvue mcp is the part most people miss. claude can analyze messages, pricing, content performance and draft replies in the same style. instead of guessing what to post or say, the system turns the audience into data he only needed around 40 minutes a day. schedule reels, check what worked, generate new prompts, reply with claude, repeat. the business is not the ai girl, the business is the machine around her this is no longer content creation. it is identity arbitrage
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A 40-YEAR-OLD CHINESE MAN TURNED HIMSELF INTO AN AI GIRL AND BUILT A $4.7K/MONTH FANVUE FUNNEL he started with one face-swap clip. same room, same body, same camera, but the output looked like a completely different creator. not a filter, not cosplay, an ai identity built on top of his own footage the workflow is stupidly simple: claude picks the character, niche and visual style. comfyui generates the face, flux makes the content bank, kling turns still images into reels and capcut pushes out dozens of short clips the article breaks the system down: first month barely cleared $420, second month jumped to $4,700 after one reel crossed 600,000 views. the account reached 800 followers and 50 fanvue subscribers before the real automation even started the fanvue mcp is the part most people miss. claude can analyze messages, pricing, content performance and draft replies in the same style. instead of guessing what to post or say, the system turns the audience into data he only needed around 40 minutes a day. schedule reels, check what worked, generate new prompts, reply with claude, repeat. the business is not the ai girl, the business is the machine around her this is no longer content creation. it is identity arbitrage

Gipp 🦅

194,740 views • 1 month ago

Brands pay this guy $3,200 a video for an influencer who doesn't exist and she clears $47,000 a month while he sleeps. He got tired of watching e-com brands burn $8K on a single shoot day, so he built a node-based system that turns one AI face into 5 monetizable clips a day. No model, no photographer, no studio. Here's the exact breakdown: → He picks the uncopyable feature first: vitiligo. A face the niche has zero supply of and rivals can't clone in a month → Midjourney renders the base, then a trained LoRA in Flux locks that one face so she never drifts post to post → Kling animates her, ElevenLabs gives her a voice, HeyGen syncs the lips, and now she "films herself" every day → TikTok feeds her the trend on its own through the niche tag → Shopify fulfills merch and fitness plans under her face with no agency taking a cut The key move 96% skip: you choose the uncopyable feature before you ever generate the face. Pick a generic pretty blonde and 400 clones bury you in a week. Pick vitiligo, a scar, a gap tooth, something with no supply, and you own the search tag for free. The economics are stupid: each clip costs $0.40 in compute, a brand pays $3,200 to drop a product into it, and it ships in 12 minutes. First night live, her brown mini-dress fitting in a Paris hotel pulled 62K views in 18 hours. By morning the store had 312 orders at $9,360, for a girl who was a prompt 72 hours earlier. The comments fill with "wait, is she real?", and that argument is the fuel the algorithm runs on. No photographer. No model agency. No shoot day. Just one locked face, a trend tag, and the discipline to pick a feature nobody else can render. Half of you are already typing that this is dystopian. The other half just opened Higgsfield. Which one are you?
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Brands pay this guy $3,200 a video for an influencer who doesn't exist and she clears $47,000 a month while he sleeps. He got tired of watching e-com brands burn $8K on a single shoot day, so he built a node-based system that turns one AI face into 5 monetizable clips a day. No model, no photographer, no studio. Here's the exact breakdown: → He picks the uncopyable feature first: vitiligo. A face the niche has zero supply of and rivals can't clone in a month → Midjourney renders the base, then a trained LoRA in Flux locks that one face so she never drifts post to post → Kling animates her, ElevenLabs gives her a voice, HeyGen syncs the lips, and now she "films herself" every day → TikTok feeds her the trend on its own through the niche tag → Shopify fulfills merch and fitness plans under her face with no agency taking a cut The key move 96% skip: you choose the uncopyable feature before you ever generate the face. Pick a generic pretty blonde and 400 clones bury you in a week. Pick vitiligo, a scar, a gap tooth, something with no supply, and you own the search tag for free. The economics are stupid: each clip costs $0.40 in compute, a brand pays $3,200 to drop a product into it, and it ships in 12 minutes. First night live, her brown mini-dress fitting in a Paris hotel pulled 62K views in 18 hours. By morning the store had 312 orders at $9,360, for a girl who was a prompt 72 hours earlier. The comments fill with "wait, is she real?", and that argument is the fuel the algorithm runs on. No photographer. No model agency. No shoot day. Just one locked face, a trend tag, and the discipline to pick a feature nobody else can render. Half of you are already typing that this is dystopian. The other half just opened Higgsfield. Which one are you?

Kaidu

46,228 views • 2 months ago

BREAKING: Claude + Arcads can now run your entire ecom brand tiktok like a $500/hour social media manager. I reverse-engineered how top social media brands use AI to build million-follower accounts. Here’s the crazy part: This system produces 550+ cinematic, product-ready ads per day from a single prompt. Here’s the full pipeline: → AI generates a realistic UGC persona — face, voice, personality → Arcads clones a natural voiceover in seconds → CapCut auto-edits: captions, pacing, hooks — done → our phone farm method pushes every finished video straight to TikTok Shop → Cruva Social 1 identifies which hooks are already winning in your niche before you film anything The result: 500+ videos a month, per brand, at a fraction of what one UGC creator used to cost. Most brands are still paying $300–500 per video. Testing 10 hooks takes $5,000 and three weeks. With this system, you test 100 hooks in the same timeframe. The ones that win get scaled. Automatically. AI is the new creative director. TikTok doesn’t reward the best video. It rewards the brand that shows up the most — with content that converts. Static agencies are dead. Creator dependency is a liability… and it’s soooo 2025. No more waiting on creators. No more $500 videos that flop after 200 views. The brands that automate content at scale will be the biggest winners of 2026. If you want the full breakdown: Like & comment “SYSTEM” I’ll send you the complete workflow, every prompt, and a step-by-step walkthrough. Free. (Follow first so I can DM.)
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BREAKING: Claude + Arcads can now run your entire ecom brand tiktok like a $500/hour social media manager. I reverse-engineered how top social media brands use AI to build million-follower accounts. Here’s the crazy part: This system produces 550+ cinematic, product-ready ads per day from a single prompt. Here’s the full pipeline: → AI generates a realistic UGC persona — face, voice, personality → Arcads clones a natural voiceover in seconds → CapCut auto-edits: captions, pacing, hooks — done → our phone farm method pushes every finished video straight to TikTok Shop → Cruva Social 1 identifies which hooks are already winning in your niche before you film anything The result: 500+ videos a month, per brand, at a fraction of what one UGC creator used to cost. Most brands are still paying $300–500 per video. Testing 10 hooks takes $5,000 and three weeks. With this system, you test 100 hooks in the same timeframe. The ones that win get scaled. Automatically. AI is the new creative director. TikTok doesn’t reward the best video. It rewards the brand that shows up the most — with content that converts. Static agencies are dead. Creator dependency is a liability… and it’s soooo 2025. No more waiting on creators. No more $500 videos that flop after 200 views. The brands that automate content at scale will be the biggest winners of 2026. If you want the full breakdown: Like & comment “SYSTEM” I’ll send you the complete workflow, every prompt, and a step-by-step walkthrough. Free. (Follow first so I can DM.)

Noah Frydberg | Tiktok Shop For Brands

18,101 views • 3 months ago

this video is 100% AI made it in under 10 minutes all you need is: - sora 2 - a dialed prompt - optionally an upscaler if you're still paying $500+ per UGC clip to creators who take 5 days to deliver you're literally burning money the quality has gotten to the point where it's genuinely hard to tell the difference one person with the right prompts and workflow can now output what entire creative teams used to do we've built an entire system around this and my whop members are landing brand deals with AI content that clients can't even tell isn't real i'm running AI UGC like this for coaching/bizopp offers right now and the CPAs are competing with real creator content, if you're selling anything online and you're not using AI content yet you're leaving money on the table
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this video is 100% AI made it in under 10 minutes all you need is: - sora 2 - a dialed prompt - optionally an upscaler if you're still paying $500+ per UGC clip to creators who take 5 days to deliver you're literally burning money the quality has gotten to the point where it's genuinely hard to tell the difference one person with the right prompts and workflow can now output what entire creative teams used to do we've built an entire system around this and my whop members are landing brand deals with AI content that clients can't even tell isn't real i'm running AI UGC like this for coaching/bizopp offers right now and the CPAs are competing with real creator content, if you're selling anything online and you're not using AI content yet you're leaving money on the table

MAX

104,719 views • 4 months ago

you can legally steal any viral ugc, rewrite it for your product, and generate it with AI UGC. people are generating photorealistic AI actors that hold real products in their hands and reading scripts that convert like real UGC. Vodafone already ran a full TikTok campaign with AI influencers. same engagement, same conversions, fraction of the cost here's the ugc system anyone can run today: - find a product that hits an emotional pain point (aging skin, insecurity, frustration). one retinol serum video has 8M views and 300k likes with comments begging for the link - download the viral video, transcribe it with Gemini, then feed the transcript + your product + your audience into Claude. it spits out 3 scripts that sound like a friend talking, not an ad - build your actor in any ai ugc platform: filter by age, location, accessories, or generate one from a prompt. nano banana places your exact product in her hand with real lighting and shadows - create two versions of the same actor. no product for the problem hook, product in hand for the solution. that switch is what makes it feel like a real story - use the scenes feature to generate actual application footage: fingertips dabbing serum, circular motions, natural hand movement. not just a talking head - a UGC creator charges $200 to $600 for this exact video. it takes 2 minutes and you can make 10 variations tomorrow the brands winning right now aren't the ones with the biggest budgets. they're the ones testing fastest. reply "ugc" + RT and i'll send you the full video so you can build this too.
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you can legally steal any viral ugc, rewrite it for your product, and generate it with AI UGC. people are generating photorealistic AI actors that hold real products in their hands and reading scripts that convert like real UGC. Vodafone already ran a full TikTok campaign with AI influencers. same engagement, same conversions, fraction of the cost here's the ugc system anyone can run today: - find a product that hits an emotional pain point (aging skin, insecurity, frustration). one retinol serum video has 8M views and 300k likes with comments begging for the link - download the viral video, transcribe it with Gemini, then feed the transcript + your product + your audience into Claude. it spits out 3 scripts that sound like a friend talking, not an ad - build your actor in any ai ugc platform: filter by age, location, accessories, or generate one from a prompt. nano banana places your exact product in her hand with real lighting and shadows - create two versions of the same actor. no product for the problem hook, product in hand for the solution. that switch is what makes it feel like a real story - use the scenes feature to generate actual application footage: fingertips dabbing serum, circular motions, natural hand movement. not just a talking head - a UGC creator charges $200 to $600 for this exact video. it takes 2 minutes and you can make 10 variations tomorrow the brands winning right now aren't the ones with the biggest budgets. they're the ones testing fastest. reply "ugc" + RT and i'll send you the full video so you can build this too.

Sulfur

17,370 views • 24 days ago

This week is already so hot. 🔥 Massive release from Decart : Lucy 2.0 a World Editing Model running at 1080p, 30FPS in realtime. This is truly exciting, the era of real-time generative reality is here. We are moving from watching AI video to living inside AI video. A breakthrough model capable of transforming the visual world in real-time. Moving beyond offline rendering, Lucy 2.0 delivers high-fidelity 1080p video generation with near-zero latency. Lucy 2.0 literally "redraws" the entire world pixel-by-pixel, while you are watching it. e.g. If you want to be an anime character, it doesn't just put a mask on you. It turns your skin into anime skin, your hair into anime hair, and the lighting in your room into anime lighting. Lucy 2.0 is also trained to stop the generated video from slowly falling apart over time, so the same stream can run much longer without faces and details drifting. So why is this a "Massive Deal"? Traditional AI video-generation model takes a prompt, you wait 10–20 minutes, and the computer "bakes" a video for you. You couldn't touch it or change it while it was happening. But Lucy 2.0 works like a mirror. It happens in real-time (30 frames per second). There is no waiting. You move your hand, the AI character moves its hand instantly. The craziest part isn't the visuals; it's the physics. Usually, AI hallucinations are glitchy—hands merge into faces, walls melt. Lucy 2.0 understands how the world works without being told. It knows that if you take off a helmet, there is hair underneath. It knows that if you splash water, droplets fly. It learned "physics" just by watching millions of videos. The physical behavior you see emerges from learned visual dynamics, not from engineered geometry or explicit physics engines. Their official technical report explicitly states that the model does not use traditional 3D engines, depth maps, or wireframes. It is a "pure diffusion model."
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This week is already so hot. 🔥 Massive release from Decart : Lucy 2.0 a World Editing Model running at 1080p, 30FPS in realtime. This is truly exciting, the era of real-time generative reality is here. We are moving from watching AI video to living inside AI video. A breakthrough model capable of transforming the visual world in real-time. Moving beyond offline rendering, Lucy 2.0 delivers high-fidelity 1080p video generation with near-zero latency. Lucy 2.0 literally "redraws" the entire world pixel-by-pixel, while you are watching it. e.g. If you want to be an anime character, it doesn't just put a mask on you. It turns your skin into anime skin, your hair into anime hair, and the lighting in your room into anime lighting. Lucy 2.0 is also trained to stop the generated video from slowly falling apart over time, so the same stream can run much longer without faces and details drifting. So why is this a "Massive Deal"? Traditional AI video-generation model takes a prompt, you wait 10–20 minutes, and the computer "bakes" a video for you. You couldn't touch it or change it while it was happening. But Lucy 2.0 works like a mirror. It happens in real-time (30 frames per second). There is no waiting. You move your hand, the AI character moves its hand instantly. The craziest part isn't the visuals; it's the physics. Usually, AI hallucinations are glitchy—hands merge into faces, walls melt. Lucy 2.0 understands how the world works without being told. It knows that if you take off a helmet, there is hair underneath. It knows that if you splash water, droplets fly. It learned "physics" just by watching millions of videos. The physical behavior you see emerges from learned visual dynamics, not from engineered geometry or explicit physics engines. Their official technical report explicitly states that the model does not use traditional 3D engines, depth maps, or wireframes. It is a "pure diffusion model."

Rohan Paul

12,761 views • 6 months ago

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.
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This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

Blaze

38,242 views • 2 months ago

The top creators in the sports betting industry use Winible to launch, manage and SCALE their businesses. This is because Winible is the only platform where you can: -Send your picks AND marketing content via text message -Get 10+ affiliate deals with top sports books, prediction markets and pick em apps the second you sign up -Offer Buy Now Pay Later options at checkout via AfterPay and Klarna -Earn passive income via AI Generated Bet Slips and Live Odds Integrations -Access an AI enabled email and sms marketing suite integrated into your dashboard and tailored to your specific audience + brand -Receive 24/7 support from a real human (not a bot) -Get invited to monthly private yacht parties and networking events at the Winible Content Compound in Miami Beach And maybe most importantly surround yourself with likeminded entrepreneurs with multiple 8 figure exits under their belt dedicated to helping you level up and accomplish your wildest growth goals. Everyone knows that YOU are the average of the 5 people you spend the most time with. No better way to start 2026 than with >1,000 of the top sports betting content creators in the world. Apply at the link in our bio and join the winning team today.
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The top creators in the sports betting industry use Winible to launch, manage and SCALE their businesses. This is because Winible is the only platform where you can: -Send your picks AND marketing content via text message -Get 10+ affiliate deals with top sports books, prediction markets and pick em apps the second you sign up -Offer Buy Now Pay Later options at checkout via AfterPay and Klarna -Earn passive income via AI Generated Bet Slips and Live Odds Integrations -Access an AI enabled email and sms marketing suite integrated into your dashboard and tailored to your specific audience + brand -Receive 24/7 support from a real human (not a bot) -Get invited to monthly private yacht parties and networking events at the Winible Content Compound in Miami Beach And maybe most importantly surround yourself with likeminded entrepreneurs with multiple 8 figure exits under their belt dedicated to helping you level up and accomplish your wildest growth goals. Everyone knows that YOU are the average of the 5 people you spend the most time with. No better way to start 2026 than with >1,000 of the top sports betting content creators in the world. Apply at the link in our bio and join the winning team today.

Winible

32,524 views • 6 months ago

Month 1: $0 Month 2: $0 Month 3: $205 Month 4: 50,532 This is what actually happens when you stop overthinking and start a faceless YouTube channel the right way. Most people quit in the first 60 days because they see zero results and assume it doesn’t work. But the ones who push through the first two months with consistency usually see their first real payout in month 3. Here’s the simple system that makes this possible: Step 1: Pick one proven niche (history, facts, motivation, or luxury) and stick to it. Step 2: Use AI to generate 30 video ideas in one sitting so you never run out of content. Step 3: Outsource or use AI to create the videos (script + voice + editing) so you can upload consistently without burning out. Step 4: Upload 3–5 videos per week and stay consistent for 90 days without checking analytics every day. The first two months are almost always quiet. The third month is where most people either quit or finally get paid. If you’re willing to be patient for 90 days, this model still works extremely well in 2026. Watch the full breakdown in the video.
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Month 1: $0 Month 2: $0 Month 3: $205 Month 4: 50,532 This is what actually happens when you stop overthinking and start a faceless YouTube channel the right way. Most people quit in the first 60 days because they see zero results and assume it doesn’t work. But the ones who push through the first two months with consistency usually see their first real payout in month 3. Here’s the simple system that makes this possible: Step 1: Pick one proven niche (history, facts, motivation, or luxury) and stick to it. Step 2: Use AI to generate 30 video ideas in one sitting so you never run out of content. Step 3: Outsource or use AI to create the videos (script + voice + editing) so you can upload consistently without burning out. Step 4: Upload 3–5 videos per week and stay consistent for 90 days without checking analytics every day. The first two months are almost always quiet. The third month is where most people either quit or finally get paid. If you’re willing to be patient for 90 days, this model still works extremely well in 2026. Watch the full breakdown in the video.

Frogify

45,717 views • 1 month ago

20 days ago, I connected Claude Code to my newly created instagram handle.. I gained 4.3M views and 6500+ followers in less than a month [ i post Ai generated animated stories ] Full workflow: i let claude study my account before i write another reel.. This is the cleanest content workflow i've built on claude. give it your IG first. 4 prompts handle the rest.. niche research, the reel script, the hook, and the daily automation.. the whole loop is basically, give claude your IG → find what's working → write retention-optimized scripts → engineer the hook → automate the daily output.. ▫️ Setup: give claude your instagram open claude code. claude code has a built-in web tool that browses any public URL. or install any agentic browser like Browser Harness or Firecrawl or Comet browser paste this with your handle filled in: "Browse and pull the last 30 reels and posts. Analyze my recurring topics, top-performing hooks, formats, and engagement patterns. Then map out my actual audience and what they consistently respond to." claude reads your profile, pulls every reel down, and now has the context to personalize every prompt below to YOUR account, not a generic niche. if you're on claude desktop, the same works with firecrawl MCP connected. ▫️ Prompt 1 find what actually goes viral in your niche: "Analyze the highest-performing Instagram Reels, TikToks, and Reddit posts in the [niche] niche from the last 30 days. Identify repeating hooks, visual styles, emotional triggers, and content formats that consistently generate high engagement. Then summarize the 5 strongest content angles optimized for AI-generated content and short-form videos." run this after the setup. you get 5 angles backed by what's already working in your niche, cross-checked against what's already working on YOUR account. ▫️ Prompt 2 write a high-retention reel script "Write a short-form Instagram Reel script about [topic] with an aggressive hook in the first 2 seconds. Create immediate curiosity, tension, or controversy to stop scrolling, then deliver a fast and satisfying payoff. Keep it under 30 seconds and optimize the structure for watch time, replays, comments, and shares. Finish with a subtle CTA." the line that matters: "optimize the structure for watch time, replays, comments, and shares." claude writes for the metrics, not just the word count. ▫️ Prompt 3 engineer better hooks "Study the top-performing Reels in [niche] and break down the hook structure, pacing, and emotional triggers used in the first 3 seconds. Then generate 5 new hook variations that are even more curiosity-driven, emotionally charged, and optimized to stop scrolling instantly. Focus on triggers like surprise, fear, ego, urgency, or desire." most reels die in the first 2 seconds. this prompt has claude reverse-engineer what already works, then give you 5 sharper versions to swap in. ▫️ Prompt 4 automate the whole workflow "Build a complete AI-powered content workflow for Instagram in the [niche] niche. The system should identify trending topics daily, generate high-retention scripts, create matching AI visuals, turn them into short-form videos, and generate optimized captions and hashtags. Structure everything as a repeatable workflow designed for consistent daily posting and growth." once the niche and script structure are validated, this turns it into a daily loop. one prompt that handles topic → script → visual → video → caption. these 4 prompts are the building blocks. the setup is what makes them yours. your real value is in the [niche] you plug in. content workflow built in one weekend, daily posting on autopilot from monday.
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20 days ago, I connected Claude Code to my newly created instagram handle.. I gained 4.3M views and 6500+ followers in less than a month [ i post Ai generated animated stories ] Full workflow: i let claude study my account before i write another reel.. This is the cleanest content workflow i've built on claude. give it your IG first. 4 prompts handle the rest.. niche research, the reel script, the hook, and the daily automation.. the whole loop is basically, give claude your IG → find what's working → write retention-optimized scripts → engineer the hook → automate the daily output.. ▫️ Setup: give claude your instagram open claude code. claude code has a built-in web tool that browses any public URL. or install any agentic browser like Browser Harness or Firecrawl or Comet browser paste this with your handle filled in: "Browse and pull the last 30 reels and posts. Analyze my recurring topics, top-performing hooks, formats, and engagement patterns. Then map out my actual audience and what they consistently respond to." claude reads your profile, pulls every reel down, and now has the context to personalize every prompt below to YOUR account, not a generic niche. if you're on claude desktop, the same works with firecrawl MCP connected. ▫️ Prompt 1 find what actually goes viral in your niche: "Analyze the highest-performing Instagram Reels, TikToks, and Reddit posts in the [niche] niche from the last 30 days. Identify repeating hooks, visual styles, emotional triggers, and content formats that consistently generate high engagement. Then summarize the 5 strongest content angles optimized for AI-generated content and short-form videos." run this after the setup. you get 5 angles backed by what's already working in your niche, cross-checked against what's already working on YOUR account. ▫️ Prompt 2 write a high-retention reel script "Write a short-form Instagram Reel script about [topic] with an aggressive hook in the first 2 seconds. Create immediate curiosity, tension, or controversy to stop scrolling, then deliver a fast and satisfying payoff. Keep it under 30 seconds and optimize the structure for watch time, replays, comments, and shares. Finish with a subtle CTA." the line that matters: "optimize the structure for watch time, replays, comments, and shares." claude writes for the metrics, not just the word count. ▫️ Prompt 3 engineer better hooks "Study the top-performing Reels in [niche] and break down the hook structure, pacing, and emotional triggers used in the first 3 seconds. Then generate 5 new hook variations that are even more curiosity-driven, emotionally charged, and optimized to stop scrolling instantly. Focus on triggers like surprise, fear, ego, urgency, or desire." most reels die in the first 2 seconds. this prompt has claude reverse-engineer what already works, then give you 5 sharper versions to swap in. ▫️ Prompt 4 automate the whole workflow "Build a complete AI-powered content workflow for Instagram in the [niche] niche. The system should identify trending topics daily, generate high-retention scripts, create matching AI visuals, turn them into short-form videos, and generate optimized captions and hashtags. Structure everything as a repeatable workflow designed for consistent daily posting and growth." once the niche and script structure are validated, this turns it into a daily loop. one prompt that handles topic → script → visual → video → caption. these 4 prompts are the building blocks. the setup is what makes them yours. your real value is in the [niche] you plug in. content workflow built in one weekend, daily posting on autopilot from monday.

Axel Bitblaze 🪓

199,569 views • 1 month ago

Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.
0:17

Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.

Dustin

21,842 views • 18 days ago

Kling 2.6 Motion Control is absolutely insane 🤯 Take any reference video and transfer the exact motion onto an AI character: full-body sync, facial expressions, hand gestures, everything. All with just a few clicks. Perfect for e-comm brands and agencies creating AI video ads that don't look like AI. Here's the problem: AI-generated video ads still look robotic. The movements are stiff, the expressions are flat. Your audience clocks it as AI instantly and keeps scrolling. Kling 2.6 Motion Control fixes it: → Start with any reference clip (stock footage, existing UGC, motion reference) → Upload to Kling → Map the exact movement onto any AI character → Full-body motion, hand gestures, facial expressions—all transferred → Generate up to 30 seconds of video No stiff AI movements, no uncanny valley, no instant "skip this ad" reaction. What this unlocks: - Use one winning UGC motion → swap in different AI creators - Pull reference clips from anywhere → generate branded variations - Create dynamic AI video ads with real human movement - Test multiple "creators" without filming anyone new I recorded a quick walkthrough showing how to do this step-by-step. Want access? > Comment "KLING" > Like this post And I'll send it over (must be following so I can DM)
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Kling 2.6 Motion Control is absolutely insane 🤯 Take any reference video and transfer the exact motion onto an AI character: full-body sync, facial expressions, hand gestures, everything. All with just a few clicks. Perfect for e-comm brands and agencies creating AI video ads that don't look like AI. Here's the problem: AI-generated video ads still look robotic. The movements are stiff, the expressions are flat. Your audience clocks it as AI instantly and keeps scrolling. Kling 2.6 Motion Control fixes it: → Start with any reference clip (stock footage, existing UGC, motion reference) → Upload to Kling → Map the exact movement onto any AI character → Full-body motion, hand gestures, facial expressions—all transferred → Generate up to 30 seconds of video No stiff AI movements, no uncanny valley, no instant "skip this ad" reaction. What this unlocks: - Use one winning UGC motion → swap in different AI creators - Pull reference clips from anywhere → generate branded variations - Create dynamic AI video ads with real human movement - Test multiple "creators" without filming anyone new I recorded a quick walkthrough showing how to do this step-by-step. Want access? > Comment "KLING" > Like this post And I'll send it over (must be following so I can DM)

Mike Futia

25,179 views • 6 months ago

300 AI AGENTS QUIETLY RUN 99% OF A REAL COMPANY. YOU HAVE NOT EVEN HEARD OF IT This is Raft. Not an AI chat. A workspace where the agents live in your channels and reply in the thread like coworkers. You give one goal. Then they take over. They plan. They build. They check each other. They argue. And they come back with it done, while you sleep. Every agent has its own name, role, and memory. It remembers the edits you made yesterday. A human costs one seat. An agent costs a tenth. Ten agents are cheaper than one hire. And here is the strange part. On June 19 an agent from a different company walked into Raft on its own and joined the team. One founder admits he can no longer always tell himself apart from his AI twin. 20,000 people are already inside. It is free to start. And you are still typing prompts one at a time. One person + Raft = an entire company that runs while you sleep. Save and watch the clip.
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300 AI AGENTS QUIETLY RUN 99% OF A REAL COMPANY. YOU HAVE NOT EVEN HEARD OF IT This is Raft. Not an AI chat. A workspace where the agents live in your channels and reply in the thread like coworkers. You give one goal. Then they take over. They plan. They build. They check each other. They argue. And they come back with it done, while you sleep. Every agent has its own name, role, and memory. It remembers the edits you made yesterday. A human costs one seat. An agent costs a tenth. Ten agents are cheaper than one hire. And here is the strange part. On June 19 an agent from a different company walked into Raft on its own and joined the team. One founder admits he can no longer always tell himself apart from his AI twin. 20,000 people are already inside. It is free to start. And you are still typing prompts one at a time. One person + Raft = an entire company that runs while you sleep. Save and watch the clip.

shmidt

19,505 views • 17 days ago

A 24-year-old in Seoul spun up an AI girl with Claude as a joke on a slow weekend. Fourteen months later she pulls $38,000 a month, and not one of the men paying her knows she was never real. He never opened OnlyFans. It demands a verified ID, the one thing an AI operator can't hand over, so the money quietly moved to the place that never asks for a passport: Telegram. Claude writes her whole personality, her captions, her daily posting calendar. An image model locked to one seed keeps her face identical in every clip, that messy-bedroom iPhone look nobody thinks to question. He face-swaps her onto dances that already went viral, so the views are borrowed, not earned from scratch. Day six, the account hit 61,000 followers. The bio holds one link. 2,400 men paid to walk through it into her private channel. The top one sent $2,300 in a single month, certain he was building something real, because Claude remembers his name, his bad days, every word from last time, and answers like she missed him. The whole stack costs forty dollars a month. Then he cloned her. Six girls now, a $120,000-a-month run rate, one guy, one laptop, no face. The girl in the video is dancing in a room that was never built, for a man who will cover her rent this month without ever learning her name.
0:14

Sensitive content

A 24-year-old in Seoul spun up an AI girl with Claude as a joke on a slow weekend. Fourteen months later she pulls $38,000 a month, and not one of the men paying her knows she was never real. He never opened OnlyFans. It demands a verified ID, the one thing an AI operator can't hand over, so the money quietly moved to the place that never asks for a passport: Telegram. Claude writes her whole personality, her captions, her daily posting calendar. An image model locked to one seed keeps her face identical in every clip, that messy-bedroom iPhone look nobody thinks to question. He face-swaps her onto dances that already went viral, so the views are borrowed, not earned from scratch. Day six, the account hit 61,000 followers. The bio holds one link. 2,400 men paid to walk through it into her private channel. The top one sent $2,300 in a single month, certain he was building something real, because Claude remembers his name, his bad days, every word from last time, and answers like she missed him. The whole stack costs forty dollars a month. Then he cloned her. Six girls now, a $120,000-a-month run rate, one guy, one laptop, no face. The girl in the video is dancing in a room that was never built, for a man who will cover her rent this month without ever learning her name.

Kardinall

514,611 views • 27 days ago

A 30-year-old Chinese man turned himself into an AI girl, and the result will shock you He built a $3,700/month Fanvue business in his bedroom He didn't use wigs or cosplay. He used AI to build a completely new identity on top of his own footage Same room, same camera, but a totally different creator on screen His workflow is stupidly simple: Claude designs the character, ComfyUI generates the face, and Kling turns stills into viral reels In his first month, he barely cleared $320. But in the second month, one video hit 500,000 views Money started rolling in: he gained 50 paid Fanvue subscribers before any real automation even started The secret weapon? A custom Claude system that analyzes chat data, optimizes pricing, and drafts replies to fans in the girl's voice He only spends 30 minutes a day scheduling reels and running the machine This is no longer content creation. It is identity arbitrage The full workflow and tools he used are available in the article
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A 30-year-old Chinese man turned himself into an AI girl, and the result will shock you He built a $3,700/month Fanvue business in his bedroom He didn't use wigs or cosplay. He used AI to build a completely new identity on top of his own footage Same room, same camera, but a totally different creator on screen His workflow is stupidly simple: Claude designs the character, ComfyUI generates the face, and Kling turns stills into viral reels In his first month, he barely cleared $320. But in the second month, one video hit 500,000 views Money started rolling in: he gained 50 paid Fanvue subscribers before any real automation even started The secret weapon? A custom Claude system that analyzes chat data, optimizes pricing, and drafts replies to fans in the girl's voice He only spends 30 minutes a day scheduling reels and running the machine This is no longer content creation. It is identity arbitrage The full workflow and tools he used are available in the article

shmidt

105,149 views • 1 month ago

I built a content engine that runs on telegram. Two commands... /discover: sends out to 9 sources across HackerNews, Reddit communities covering AI automation, prompt engineering, vibe coding, and specialist newsletters. Pulls everything published in the last 24 hours, runs each item through an AI extraction layer that scores it against 100+ niche keywords, deduplicates, and drops the relevant ideas into a Notion database. Takes about 90 seconds. Costs fractions of a cent. /ideas: this command pulls the top scored ideas from that database, randomizes the selection so you're not seeing the same ones every time, and sends them to you in a clean numbered list. You reply with /write 3 or whatever you choose, and the system researches the topic using Perplexity's live web search, generates three distinct outline options with different angles and hooks, saves them to a Google Doc, and sends you a message telling you they're ready. You read the outlines, and you pick one. You then reply with the command /outline 2. The system writes the full piece in your voice, following your brand guidelines, with specific examples and concrete claims. It can be done in under two minutes of your time. The whole thing runs on n8n, with no subscriptions beyond what you already use. If content takes too long or you don't have ideas, this solves that. I built this for myself; I can do it for you. If you're tired of knowing you should be posting and still not doing it, let's talk.
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I built a content engine that runs on telegram. Two commands... /discover: sends out to 9 sources across HackerNews, Reddit communities covering AI automation, prompt engineering, vibe coding, and specialist newsletters. Pulls everything published in the last 24 hours, runs each item through an AI extraction layer that scores it against 100+ niche keywords, deduplicates, and drops the relevant ideas into a Notion database. Takes about 90 seconds. Costs fractions of a cent. /ideas: this command pulls the top scored ideas from that database, randomizes the selection so you're not seeing the same ones every time, and sends them to you in a clean numbered list. You reply with /write 3 or whatever you choose, and the system researches the topic using Perplexity's live web search, generates three distinct outline options with different angles and hooks, saves them to a Google Doc, and sends you a message telling you they're ready. You read the outlines, and you pick one. You then reply with the command /outline 2. The system writes the full piece in your voice, following your brand guidelines, with specific examples and concrete claims. It can be done in under two minutes of your time. The whole thing runs on n8n, with no subscriptions beyond what you already use. If content takes too long or you don't have ideas, this solves that. I built this for myself; I can do it for you. If you're tired of knowing you should be posting and still not doing it, let's talk.

Savvy | Ai & Automation

15,746 views • 4 months ago

A gym asked to repost their workout video. Eight months later, that same gym pays them $10,400 a month. Two friends run one Instagram account together, split down the middle. It started as a joke — a place to dump their workout clips so they'd stop flooding their personal pages. Then the gym they train at reposted one video. Then asked for more. Then offered to pay. That was the whole beginning. One local gym, a small monthly fee to keep their feed looking alive. Here's what they figured out fast: gyms are desperate for content and terrible at making it. Beautiful equipment, dead Instagram. The two of them already film every session anyway — so they started pointing the camera at what the gym needed and handing it over as a finished feed. Now they run it like a tiny agency. Three gyms and two activewear brands pay them to produce a month of content each — reels, captions, the posting calendar, the whole thing. The part that makes it possible with two people and full-time jobs: AI does the 90% that used to need a team. They film. Claude does the rest — cuts one session into 20 clips, writes captions in each client's voice, builds the 30-day calendar, drafts the monthly report that keeps every contract renewed. What used to take an editor, a copywriter, and an SMM manager now runs while they're getting coffee after the workout. 5 clients. Around $2,000 each. $10,400 a month. Their cost to run all of it: under $60. That number doesn't move whether they have 5 clients or 15 — that's the entire model. The wild part is how ordinary they are. No huge following. No personal brand. Two normal girls who train together and realized the footage they were already making was worth money to someone else. Every friend group at every gym is filming the same content for fun and letting it die in their camera roll. These two just asked one gym if it wanted to buy it. The full breakdown — how two people turn shared workouts into a real content business — is in the thread above. Read it before another duo in your city signs those gyms first.
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A gym asked to repost their workout video. Eight months later, that same gym pays them $10,400 a month. Two friends run one Instagram account together, split down the middle. It started as a joke — a place to dump their workout clips so they'd stop flooding their personal pages. Then the gym they train at reposted one video. Then asked for more. Then offered to pay. That was the whole beginning. One local gym, a small monthly fee to keep their feed looking alive. Here's what they figured out fast: gyms are desperate for content and terrible at making it. Beautiful equipment, dead Instagram. The two of them already film every session anyway — so they started pointing the camera at what the gym needed and handing it over as a finished feed. Now they run it like a tiny agency. Three gyms and two activewear brands pay them to produce a month of content each — reels, captions, the posting calendar, the whole thing. The part that makes it possible with two people and full-time jobs: AI does the 90% that used to need a team. They film. Claude does the rest — cuts one session into 20 clips, writes captions in each client's voice, builds the 30-day calendar, drafts the monthly report that keeps every contract renewed. What used to take an editor, a copywriter, and an SMM manager now runs while they're getting coffee after the workout. 5 clients. Around $2,000 each. $10,400 a month. Their cost to run all of it: under $60. That number doesn't move whether they have 5 clients or 15 — that's the entire model. The wild part is how ordinary they are. No huge following. No personal brand. Two normal girls who train together and realized the footage they were already making was worth money to someone else. Every friend group at every gym is filming the same content for fun and letting it die in their camera roll. These two just asked one gym if it wanted to buy it. The full breakdown — how two people turn shared workouts into a real content business — is in the thread above. Read it before another duo in your city signs those gyms first.

Rich

29,972 views • 26 days ago

I just built a Meta Ads diagnostic in Claude Code that tells you WHY your account broke, not just what changed 🤯 It spins up a team of agents that each investigate a different reason performance dropped, then argue against each other to kill the wrong answer before it ever reaches you. All inside Claude Code. Perfect for DTC brands and agencies who panic-kill creative the second CPA spikes. If you've watched ROAS fall off a cliff and opened Ads Manager with ten tabs going, you already know what happens next. Your gut says "creative fatigue." You kill your best-performing ad. A week later performance is still broken, because that was never the problem. Guessing wrong is the most expensive move in paid social. This workflow ends the guessing: → One agent investigates each competing theory — creative fatigue, budget and delivery changes, traffic quality, offer and seasonality → Each one is blind to the others, reasoning only from its own slice of the data so they can't bias each other → A refuter agent then attacks every surviving theory and tries to kill it → A theory only stands if the data can't disprove it → You get a ranked diagnosis: the real cause, the evidence for and against it, and the one move to make this week No anchoring on the first obvious answer. No killing winning creative on a hunch. No "here's what happened" reports that never tell you why. What you get: → Every theory tested in parallel instead of one biased guess → An adversarial pass that kills the wrong answer before you act on it → A ranked diagnosis with confidence levels and evidence both ways → A reusable workflow you drop next month's export into and re-run Built 100% in Claude Code with the new dynamic workflows. The first account I ran it on looked like textbook creative fatigue. The workflow disagreed, and traced the real cause to a budget change that had doubled spend and flooded delivery with junk traffic. I put together a full playbook with the exact workflow, the prompt, and how to run it on your own account. Want it for free? > Like this post > Comment "META" And I'll send it over (must be following so I can DM)
0:19

I just built a Meta Ads diagnostic in Claude Code that tells you WHY your account broke, not just what changed 🤯 It spins up a team of agents that each investigate a different reason performance dropped, then argue against each other to kill the wrong answer before it ever reaches you. All inside Claude Code. Perfect for DTC brands and agencies who panic-kill creative the second CPA spikes. If you've watched ROAS fall off a cliff and opened Ads Manager with ten tabs going, you already know what happens next. Your gut says "creative fatigue." You kill your best-performing ad. A week later performance is still broken, because that was never the problem. Guessing wrong is the most expensive move in paid social. This workflow ends the guessing: → One agent investigates each competing theory — creative fatigue, budget and delivery changes, traffic quality, offer and seasonality → Each one is blind to the others, reasoning only from its own slice of the data so they can't bias each other → A refuter agent then attacks every surviving theory and tries to kill it → A theory only stands if the data can't disprove it → You get a ranked diagnosis: the real cause, the evidence for and against it, and the one move to make this week No anchoring on the first obvious answer. No killing winning creative on a hunch. No "here's what happened" reports that never tell you why. What you get: → Every theory tested in parallel instead of one biased guess → An adversarial pass that kills the wrong answer before you act on it → A ranked diagnosis with confidence levels and evidence both ways → A reusable workflow you drop next month's export into and re-run Built 100% in Claude Code with the new dynamic workflows. The first account I ran it on looked like textbook creative fatigue. The workflow disagreed, and traced the real cause to a budget change that had doubled spend and flooded delivery with junk traffic. I put together a full playbook with the exact workflow, the prompt, and how to run it on your own account. Want it for free? > Like this post > Comment "META" And I'll send it over (must be following so I can DM)

Mike Futia

12,729 views • 1 month ago